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Understanding big data : analytics for enterprise class Hadoop and streaming data

Understanding big data : analytics for enterprise class Hadoop and streaming data

자료유형
단행본
개인저자
Zikopoulos, Paul.
서명 / 저자사항
Understanding big data : analytics for enterprise class Hadoop and streaming data / Paul C. Zikopoulos ... [et al.].
발행사항
New York :   McGraw-Hill,   2012.  
형태사항
xxxi, 141 p. : ill. ; 23 cm.
ISBN
9780071790536 (pbk.) 0071790535 (pbk.)
요약
"Big Data represents a new era in data exploration and utilization, and IBM is uniquely positioned to help clients navigate this transformation. This book reveals how IBM is leveraging open source Big Data technology, infused with IBM technologies, to deliver a robust, secure, highly available, enterprise-class Big Data platform. The three defining characteristics of Big Data-volume, variety, and velocity-are discussed. You'll get a primer on Hadoop and how IBM is hardening it for the enterprise, and learn when to leverage IBM InfoSphere BigInsights (Big Data at rest) and IBM InfoSphere Streams (Big Data in motion) technologies. Industry use cases are also included in this practical guide."--
일반주제명
Electronic data processing --Distributed processing. File organization (Computer science). Data mining.
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020 ▼a 9780071790536 (pbk.)
020 ▼a 0071790535 (pbk.)
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245 0 0 ▼a Understanding big data : ▼b analytics for enterprise class Hadoop and streaming data / ▼c Paul C. Zikopoulos ... [et al.].
260 ▼a New York : ▼b McGraw-Hill, ▼c 2012.
300 ▼a xxxi, 141 p. : ▼b ill. ; ▼c 23 cm.
520 ▼a "Big Data represents a new era in data exploration and utilization, and IBM is uniquely positioned to help clients navigate this transformation. This book reveals how IBM is leveraging open source Big Data technology, infused with IBM technologies, to deliver a robust, secure, highly available, enterprise-class Big Data platform. The three defining characteristics of Big Data-volume, variety, and velocity-are discussed. You'll get a primer on Hadoop and how IBM is hardening it for the enterprise, and learn when to leverage IBM InfoSphere BigInsights (Big Data at rest) and IBM InfoSphere Streams (Big Data in motion) technologies. Industry use cases are also included in this practical guide."-- ▼c Page 4 of cover.
630 0 0 ▼a Apache Hadoop (Computer file).
650 0 ▼a Electronic data processing ▼x Distributed processing.
650 0 ▼a File organization (Computer science).
650 0 ▼a Data mining.
700 1 ▼a Zikopoulos, Paul.
945 ▼a KLPA

소장정보

No. 소장처 청구기호 등록번호 도서상태 반납예정일 예약 서비스
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컨텐츠정보

저자소개

Paul C. Zikopoulos(지은이)

Chris Eaton(지은이)

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